{"id":"W2058730087","doi":"10.1016/j.clim.2010.11.012","title":"Strategy for anti-aquaporin-4 auto-antibody identification and quantification using a new cell-based assay","year":2010,"lang":"en","type":"article","venue":"Clinical Immunology","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Centre Hospitalier Régional Universitaire de Montpellier","keywords":"IIf; Neuromyelitis optica; Aquaporin 4; Antibody; Indirect immunofluorescence; Identification (biology); Autoantibody; Biomarker; Immunology; Medicine; Biology; Internal medicine; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001907568,0.002407375,0.001870103,0.002392997,0.0007543173,0.001326014,0.001893396,0.002010426,0.003723226],"category_scores_gemma":[0.00191991,0.001126396,0.001142013,0.0007058242,0.0009393507,0.0008350521,0.002100633,0.003676189,0.00516715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005624198,"about_ca_system_score_gemma":0.0006551304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006369848,"about_ca_topic_score_gemma":0.001157683,"domain_scores_codex":[0.9968764,0.001146224,0.0003121771,0.0005509079,0.0007636972,0.0003507137],"domain_scores_gemma":[0.9978802,0.0008743585,0.0001217123,0.0004072707,0.0005475176,0.0001688922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00016306,0.0002133224,0.0005097727,0.0001074271,0.00004053639,0.00005818737,0.00007167114,0.0001602923,0.9896998,0.0007297142,0.0003983863,0.007847841],"study_design_scores_gemma":[0.0001034141,0.0009517584,0.002704566,0.00003855366,0.0001759889,0.0007257626,0.00008424057,0.01396095,0.9668387,0.001356928,0.0129836,0.00007543308],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1081597,0.002367273,0.8743799,0.0007148171,0.0007859787,0.002346834,0.001096811,0.001470253,0.00867852],"genre_scores_gemma":[0.3176893,0.002222239,0.6511274,0.001559017,0.0004369584,0.007017198,0.004011157,0.0002530132,0.01568366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003723226,"threshold_uncertainty_score":0.01245546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2214725031096153,"score_gpt":0.4902006623578841,"score_spread":0.2687281592482688,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}